CODEWITHSUNDEEP
pythonscikit-learnregression
Hanan Shteingart
Hanan Shteingart

Reputation: 9078

sklearn LogisticRegression without regularization

Logistic regression class in sklearn comes with L1 and L2 regularization. How can I turn off regularization to get the "raw" logistic fit such as in glmfit in Matlab? I think I can set C = large number but I don't think it is wise.

see for more details the documentation http://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html#sklearn.linear_model.LogisticRegression

Upvotes: 23

Views: 19072

Answers (2)

Yu Chen
Yu Chen

Reputation: 7460

Yes, choose as large a number as possible. In regularization, the cost function includes a regularization expression, and keep in mind that the C parameter in sklearn regularization is the inverse of the regularization strength.

C in this case is 1/lambda, subject to the condition that C > 0.

Therefore, when C approaches infinity, then lambda approaches 0. When this happens, then the cost function becomes your standard error function, since the regularization expression becomes, for all intents and purposes, 0.

Update: In sklearn versions 0.21 and higher, you can disable regularization by passing in penalty='none'. Check out the documentation here.

Upvotes: 9

Phillip Chilton Adkins
Phillip Chilton Adkins

Reputation: 101

Go ahead and set C as large as you please. Also, make sure to use l2 since l1 with that implementation can be painfully slow.

Upvotes: 6

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